Kevin P. Nguyen

Orcid: 0000-0001-5520-7285

According to our database1, Kevin P. Nguyen authored at least 12 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
Adversarially-Regularized Mixed Effects Deep Learning (ARMED) Models Improve Interpretability, Performance, and Generalization on Clustered (non-iid) Data.
IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

BLENDS: Augmentation of Functional Magnetic Resonance Images for Machine Learning Using Anatomically Constrained Warping.
Brain Connect., March, 2023

2022
Pitfalls and Recommended Strategies and Metrics for Suppressing Motion Artifacts in Functional MRI.
Neuroinformatics, 2022

UQ-ARMED: Uncertainty quantification of adversarially-regularized mixed effects deep learning for clustered non-iid data.
CoRR, 2022

Adversarially-regularized mixed effects deep learning (ARMED) models for improved interpretability, performance, and generalization on clustered data.
CoRR, 2022

2020
Anatomically informed data augmentation for functional MRI with applications to deep learning.
Proceedings of the Medical Imaging 2020: Image Processing, 2020

Improved motion correction for functional MRI using an omnibus regression model.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Architectural configurations, atlas granularity and functional connectivity with diagnostic value in Autism Spectrum Disorder.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Prediction of Individual Progression Rate in Parkinson's Disease Using Clinical Measures and Biomechanical Measures of Gait and Postural Stability.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Predicting Response to the Antidepressant Bupropion Using Pretreatment fMRI.
Proceedings of the Predictive Intelligence in Medicine - Second International Workshop, 2019

Sensitivity of Derived Clinical Biomarkers to rs-fMRI Preprocessing Software Versions.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Multiple Deep Learning Architectures Achieve Superior Performance Diagnosing Autism Spectrum Disorder Using Features Previously Extracted From Structural And Functional Mri.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019


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